2,682 research outputs found
Block synchronization for quantum information
Locating the boundaries of consecutive blocks of quantum information is a
fundamental building block for advanced quantum computation and quantum
communication systems. We develop a coding theoretic method for properly
locating boundaries of quantum information without relying on external
synchronization when block synchronization is lost. The method also protects
qubits from decoherence in a manner similar to conventional quantum
error-correcting codes, seamlessly achieving synchronization recovery and error
correction. A family of quantum codes that are simultaneously synchronizable
and error-correcting is given through this approach.Comment: 7 pages, no figures, final accepted version for publication in
Physical Review
Exclusive development of T cell neoplasms in mice transplanted with bone marrow expressing activated Notch alleles
Notch is a highly conserved transmembrane protein that is involved in cell fate decisions and is found in organisms ranging from Drosophila to humans. A human homologue of Notch, TAN1, was initially identified at the chromosomal breakpoint of a subset of T-cell lymphoblastic leukemias/lymphomas containing a t(7;9) chromosomal translocation; however, its role in oncogenesis has been unclear. Using a bone marrow reconstitution assay with cells containing retrovirally transduced TAN1 alleles, we analyzed the oncogenic potential of both nuclear and extranuclear forms of truncated TAN1 in hematopoietic cells. Although the Moloney leukemia virus long terminal repeat drives expression in most hematopoietic cell types, retroviruses encoding either form of the TAN1 protein induced clonal leukemias of exclusively immature T cell phenotypes in approximately 50% of transplanted animals. All tumors overexpressed truncated TAN1 of the size and subcellular localization predicted from the structure of the gene. These results show that TAN1 is an oncoprotein and suggest that truncation and overexpression are important determinants of transforming activity. Moreover, the murine tumors caused by TAN1 in the bone marrow transplant model are very similar to the TAN1-associated human tumors and suggest that TAN1 may be specifically oncotropic for T cells
Testing fluvial erosion models using the transient response of bedrock rivers to tectonic forcing in the Apennines, Italy
The transient response of bedrock rivers to a drop in base level can be used to
discriminate between competing fluvial erosion models. However, some recent studies of
bedrock erosion conclude that transient river long profiles can be approximately
characterized by a transportâlimited erosion model, while other authors suggest that a
detachmentâlimited model best explains their field data. The difference is thought to be
due to the relative volume of sediment being fluxed through the fluvial system. Using a
pragmatic approach, we address this debate by testing the ability of endâmember fluvial
erosion models to reproduce the wellâdocumented evolution of three catchments in the
central Apennines (Italy) which have been perturbed to various extents by an
independently constrained increase in relative uplift rate. The transportâlimited model is
unable to account for the catchmentsâresponse to the increase in uplift rate, consistent with
the observed low rates of sediment supply to the channels. Instead, a detachmentâlimited
model with a threshold corresponding to the fieldâderived median grain size of the
sediment plus a slopeâdependent channel width satisfactorily reproduces the overall
convex long profiles along the studied rivers. Importantly, we find that the prefactor in the
hydraulic scaling relationship is uplift dependent, leading to landscapes responding faster
the higher the uplift rate, consistent with field observations. We conclude that a slopeâ
dependent channel width and an entrainment/erosion threshold are necessary ingredients
when modeling landscape evolution or mapping the distribution of fluvial erosion rates in
areas where the rate of sediment supply to channels is low
Predicting the temporal activity patterns of new venues.
Estimating revenue and business demand of a newly opened venue is paramount
as these early stages often involve critical decisions such as first rounds of staffing
and resource allocation. Traditionally, this estimation has been performed through
coarse-grained measures such as observing numbers in local venues or venues at
similar places (e.g., coffee shops around another station in the same city). The
advent of crowdsourced data from devices and services carried by individuals on a
daily basis has opened up the possibility of performing better predictions of
temporal visitation patterns for locations and venues. In this paper, using mobility
data from Foursquare, a location-centric platform, we treat venue categories as
proxies for urban activities and analyze how they become popular over time. The
main contribution of this work is a prediction framework able to use characteristic
temporal signatures of places together with k-nearest neighbor metrics capturing
similarities among urban regions, to forecast weekly popularity dynamics of a new
venue establishment in a city neighborhood. We further show how we are able to
forecast the popularity of the new venue after one month following its opening by
using locality and temporal similarity as features. For the evaluation of our
approach we focus on London. We show that temporally similar areas of the city
can be successfully used as inputs of predictions of the visit patterns of new
venues, with an improvement of 41% compared to a random selection of wards as
a training set for the prediction task. We apply these concepts of temporally
similar areas and locality to the real-time predictions related to new venues and
show that these features can effectively be used to predict the future trends of a
venue. Our findings have the potential to impact the design of location-based
technologies and decisions made by new business owners
One-Pot Synthesis of 2-Methylfurans from 3- (Trimethylsilyl)propargyl Acetates Promoted by Trimethylsilyl Trifluoromethanesulfonate
In the presence of trimethylsilyl trifluoromethanesulfonate (TMSOTf) and triethylamine, 3-(trimethylsilyl)propargyl carboxylates undergo a one-pot alkylation-cyclization- desilylation reaction with ketones to produce 2-methylfurans. Alkylation at 0 °C in methylene chloride, followed by acid-catalyzed cyclization at room temperature, provides the furans in 52-86% yield. Cyclization and desilylation appear to be promoted by triflic acid generated in situ from the exposure of the reaction mixture to water upon completion of the initial substitution reaction
An Alternative Interpretation of Statistical Mechanics
In this paper I propose an interpretation of classical statistical mechanics that centers on taking seriously the idea that probability measures represent complete states of statistical mechanical systems. I show how this leads naturally to the idea that the stochasticity of statistical mechanics is associated directly with the observables of the theory rather than with the microstates (as traditional accounts would have it). The usual assumption that microstates are representationally significant in the theory is therefore dispensable, a consequence which suggests interesting possibilities for developing non-equilibrium statistical mechanics and investigating inter-theoretic answers to the foundational questions of statistical mechanics
Predicting the temporal activity patterns of new venues
Estimating revenue and business demand of a newly opened venue is paramount as these early stages often involve critical decisions such as first rounds of staffing and resource allocation. Traditionally, this estimation has been performed through coarse-grained measures such as observing numbers in local venues or venues at similar places (e.g., coffee shops around another station in the same city). The advent of crowdsourced data from devices and services carried by individuals on a daily basis has opened up the possibility of performing better predictions of temporal visitation patterns for locations and venues. In this paper, using mobility data from Foursquare, a location-centric platform, we treat venue categories as proxies for urban activities and analyze how they become popular over time. The main contribution of this work is a prediction framework able to use characteristic temporal signatures of places together with k-nearest neighbor metrics capturing similarities among urban regions, to forecast weekly popularity dynamics of a new venue establishment in a city neighborhood. We further show how we are able to forecast the popularity of the new venue after one month following its opening by using locality and temporal similarity as features. For the evaluation of our approach we focus on London. We show that temporally similar areas of the city can be successfully used as inputs of predictions of the visit patterns of new venues, with an improvement of 41% compared to a random selection of wards as a training set for the prediction task. We apply these concepts of temporally similar areas and locality to the real-time predictions related to new venues and show that these features can effectively be used to predict the future trends of a venue. Our findings have the potential to impact the design of location-based technologies and decisions made by new business owners
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